Energy-Aware Optimal Reconfiguration of a Heterogeneous Connected and Automated Vehicle Cohort on a Limited-Access Highway

This paper presents an optimized vehicular reordering methodology designed to minimize energy consumption within heterogeneous cohorts operating at constant velocity on limited-access highways. The approach addresses the challenge of optimizing vehicle sequencing by considering both aerodynamic drag reduction benefits and the energy costs of reconfiguring a cohort from a stochastic initial state. This study provides empirical validation through on-road vehicle tests, demonstrating significant energy savings, achieving up to 10% reduction in axle energy for optimally configured cohorts compared to independent operation. A System of Systems (SoS) simulation environment, integrating micro-traffic, validated powertrain, and aerodynamic drag reduction models, was developed to simulate complex reconfiguration maneuvers and quantify associated energy expenditures. The methodology examines how powertrain characteristics influence optimal arrangements and quantifies the impact of individual vehicle placement on overall cohort efficiency. Findings indicate that while reconfiguration incurs a minor energy cost (typically <0.45% of total trip energy for a 20 km trip), the net energy savings over relevant travel distances are substantial. The study also highlights the sensitivity of drag reduction estimators for heterogeneous platoons and the current limitations in available models. Ultimately, a predictive optimization framework is proposed that leverages connectivity-enabled information to select the most energy-efficient cohort configuration, considering factors such as distance to destination and reconfiguration energy, thereby offering a practical strategy for enhancing fuel economy in future connected and automated transportation systems.